3D Mesh Shape Refinement via Artifact Removal and Hole Filling
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Solution Overview
Problem
Manual refinement of 3D meshes for realistic object representation in computer graphics is time-consuming and prone to errors, especially in applications like virtual reality and gaming where photorealism is crucial.
Innovation Solution
An electronic device and method for automated shape refinement of 3D meshes reconstructed from images, involving image acquisition, removal of unneeded regions and artifacts, hole filling, and remeshing to generate a refined 3D mesh with improved accuracy and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual refinement is used to remove artifacts and defects from 3D mesh, then the quality and realism of the 3D model is improved, but the time consumption and labor effort increase significantly
Solution Approach 1:
The system performs automated self-refinement of the 3D mesh by identifying and removing artifacts, filling holes, and optimizing geometry without requiring manual intervention. The electronic device executes algorithms that autonomously analyze the mesh structure, detect defects based on geometric criteria, and apply appropriate refinement operations, thereby eliminating the need for time-consuming manual refinement while maintaining high mesh quality
Solution Approach 2:
The patent replaces the manual mechanical refinement process with an automated computational system. Instead of relying on human operators to visually inspect and manually adjust mesh geometry, the system uses image processing algorithms and geometric analysis to automatically detect artifacts, classify hole types, and apply mathematical operations for mesh optimization, thereby substituting manual labor with automated computational mechanisms
2Manufacturing precision
If manual refinement is used to correct defects in 3D mesh, then the accuracy of the 3D model is improved, but the process becomes prone to human errors
Solution Approach 1:
The automated system performs consistent, rule-based refinement operations without human intervention, eliminating variability and errors associated with manual processes. The electronic device executes deterministic algorithms that systematically analyze mesh geometry and apply standardized refinement techniques, ensuring reliable and reproducible results across different 3D models without the pitfalls of human error
Solution Approach 2:
The system incorporates feedback mechanisms where the refinement process continuously monitors the 3D mesh quality metrics and adjusts operations accordingly. By analyzing the geometric properties and detecting artifacts through automated image processing, the system provides real-time feedback to guide refinement decisions, ensuring accurate and reliable correction of mesh defects without manual intervention
3Manufacturing precision
If detailed 3D mesh refinement is performed to achieve photorealism, then the visual quality is improved, but the computational complexity and processing requirements increase
Solution Approach 1:
The patent segments the 3D mesh refinement process into distinct operational phases: artifact detection, hole classification, boundary refinement, and geometry optimization. By dividing the complex refinement task into manageable segments, the system can apply specialized algorithms to each phase independently, reducing overall computational complexity while achieving photorealistic visual quality through systematic processing
Solution Approach 2:
The system applies localized refinement operations to specific regions of the 3D mesh based on detected artifact locations and hole characteristics. Instead of uniformly processing the entire mesh, the electronic device identifies problem areas and applies targeted refinement techniques only where needed, thereby reducing computational complexity while maintaining high visual realism in critical regions
Data Source
AI summary
An electronic device and method for shape refinement of a 3D mesh reconstructed from images is disclosed. A set of images of an object is acquired and used to estimate a first 3D mesh of a head portion of the object. A first set of operations is executed on the first 3D mesh to generate a second 3D mesh. The first set of operations includes a removal of one or more regions which are unneeded for head-shape estimation and/or a removal of one or more mesh artifacts associated with a 3D shape or a topology of the first 3D mesh. A 3D template mesh is processed to determine a set of filling patches which corresponds to a set of holes in the second 3D mesh. Based on the second 3D mesh and the set of filling patches, a hole filling operation is executed to generate a final 3D mesh.